Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150872
Title: Secure estimation for attitude and heading reference systems under sparse attacks
Authors: Jiang, Rui
Liu, Xinghua
Wang, Han
Ge, Shuzhi Sam
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2019
Source: Jiang, R., Liu, X., Wang, H. & Ge, S. S. (2019). Secure estimation for attitude and heading reference systems under sparse attacks. IEEE Sensors Journal, 19(2), 641-649. https://dx.doi.org/10.1109/JSEN.2018.2877521
Journal: IEEE Sensors Journal
Abstract: This paper focuses on the problem of secure attitude estimation for autonomous vehicles. Based on the established AHRS measuring model and the attack model, we have decomposed the optimal Kalman estimate into a linear combination of local state estimates. We then propose a convex optimization-based approach, instead of the weighted sum approach, to combine the local estimate into a more secure estimate. It is shown that the proposed secure estimator coincides with the Kalman estimator with certain probability when there is no attack, and can be stable when p elements of the model state are compromised. Simulations have been conducted to validate the proposed secure filter under single and multiple measurement attacks.
URI: https://hdl.handle.net/10356/150872
ISSN: 1530-437X
DOI: 10.1109/JSEN.2018.2877521
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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